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segformer-b0-finetuned-serra-do-cipo-tiled-final
Wallksss/segformer-b0-finetuned-serra-do-cipo-tiled-final
segformer-b0-finetuned-serra-do-cipo-tiled-final is a image segmentation model from Wallksss. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Segmentation
- Library
- transformers
- License
- other
- Model type
- segformer
- Access
- Public
- Created
- Oct 15, 2025
- Updated
- Oct 15, 2025
- SHA
- 6c53c89c
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
segformer-b0-finetuned-serra-do-cipo-tiled-final
This model is a fine-tuned version of nvidia/mit-b0 on the Wallksss/Serra_do_Cipo dataset. It achieves the following results on the evaluation set:
- Loss: 0.0742
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.7608 | 1.0 | 18 | 1.5904 |
| 1.3493 | 2.0 | 36 | 1.5500 |
| 1.0919 | 3.0 | 54 | 1.2765 |
| 1.1371 | 4.0 | 72 | 1.1125 |
| 0.8422 | 5.0 | 90 | 0.8438 |
| 0.7513 | 6.0 | 108 | 0.7143 |
| 0.6757 | 7.0 | 126 | 0.7517 |
| 0.6331 | 8.0 | 144 | 0.6190 |
| 0.5039 | 9.0 | 162 | 0.5626 |
| 0.4162 | 10.0 | 180 | 0.4932 |
| 0.3874 | 11.0 | 198 | 0.3817 |
| 0.3531 | 12.0 | 216 | 0.3511 |
| 0.2899 | 13.0 | 234 | 0.3011 |
| 0.2401 | 14.0 | 252 | 0.4051 |
| 0.2052 | 15.0 | 270 | 0.3022 |
| 0.1919 | 16.0 | 288 | 0.2634 |
| 0.168 | 17.0 | 306 | 0.2085 |
| 0.1416 | 18.0 | 324 | 0.2597 |
| 0.1223 | 19.0 | 342 | 0.1371 |
| 0.1185 | 20.0 | 360 | 0.2311 |
| 0.1091 | 21.0 | 378 | 0.1294 |
| 0.0942 | 22.0 | 396 | 0.1210 |
| 0.0848 | 23.0 | 414 | 0.1088 |
| 0.0788 | 24.0 | 432 | 0.1133 |
| 0.0762 | 25.0 | 450 | 0.0987 |
| 0.0791 | 26.0 | 468 | 0.0943 |
| 0.0675 | 27.0 | 486 | 0.0978 |
| 0.0677 | 28.0 | 504 | 0.1074 |
| 0.0609 | 29.0 | 522 | 0.0827 |
| 0.0599 | 30.0 | 540 | 0.1010 |
| 0.0629 | 31.0 | 558 | 0.0800 |
| 0.0588 | 32.0 | 576 | 0.0796 |
| 0.0544 | 33.0 | 594 | 0.0773 |
| 0.0514 | 34.0 | 612 | 0.0852 |
| 0.0518 | 35.0 | 630 | 0.0822 |
| 0.0505 | 36.0 | 648 | 0.0837 |
| 0.0493 | 37.0 | 666 | 0.0765 |
| 0.0503 | 38.0 | 684 | 0.0724 |
| 0.0477 | 39.0 | 702 | 0.0750 |
| 0.0479 | 40.0 | 720 | 0.0701 |
| 0.0433 | 41.0 | 738 | 0.0852 |
| 0.045 | 42.0 | 756 | 0.0639 |
| 0.0466 | 43.0 | 774 | 0.0694 |
| 0.0438 | 44.0 | 792 | 0.0747 |
| 0.0419 | 45.0 | 810 | 0.0781 |
| 0.043 | 46.0 | 828 | 0.0693 |
| 0.0438 | 47.0 | 846 | 0.0742 |
| 0.0453 | 48.0 | 864 | 0.0731 |
| 0.0409 | 49.0 | 882 | 0.0680 |
| 0.0413 | 50.0 | 900 | 0.0742 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Image Segmentation
- Library
- transformers
- Type
- segformer
- License
- other
- Created
- Oct 15, 2025
- Updated
- Oct 15, 2025